TY - GEN
T1 - How We Swipe
T2 - 23rd ACM International Conference on Mobile Human-Computer Interaction: Mobile Apart, MobileTogether, MobileHCI 2021
AU - Leiva, Luis A.
AU - Kim, Sunjun
AU - Cui, Wenzhe
AU - Bi, Xiaojun
AU - Oulasvirta, Antti
N1 - Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/9/27
Y1 - 2021/9/27
N2 - Despite the prevalence of shape-writing (gesture typing, swype input, or swiping for short) as a text entry method, there are currently no public datasets available. We report a large-scale dataset that can support efforts in both empirical study of swiping as well as the development of better intelligent text entry techniques. The dataset was collected via a web-based custom virtual keyboard, involving 1,338 users who submitted 11,318 unique English words. We report aggregate-level indices on typing performance, user-related factors, as well as trajectory-level data, such as the gesture path drawn on top of the keyboard or the time lapsed between consecutively swiped keys. We find some well-known effects reported in previous studies, for example that speed and error are affected by age and language skill. We also find surprising relationships such that, on large screens, swipe trajectories are longer but people swipe faster.
AB - Despite the prevalence of shape-writing (gesture typing, swype input, or swiping for short) as a text entry method, there are currently no public datasets available. We report a large-scale dataset that can support efforts in both empirical study of swiping as well as the development of better intelligent text entry techniques. The dataset was collected via a web-based custom virtual keyboard, involving 1,338 users who submitted 11,318 unique English words. We report aggregate-level indices on typing performance, user-related factors, as well as trajectory-level data, such as the gesture path drawn on top of the keyboard or the time lapsed between consecutively swiped keys. We find some well-known effects reported in previous studies, for example that speed and error are affected by age and language skill. We also find surprising relationships such that, on large screens, swipe trajectories are longer but people swipe faster.
KW - Dataset
KW - Gesture Typing
KW - Phrase set
KW - Shape-writing
KW - Swiping
KW - Text Entry
UR - https://www.scopus.com/pages/publications/85117299465
U2 - 10.1145/3447526.3472059
DO - 10.1145/3447526.3472059
M3 - Conference contribution
AN - SCOPUS:85117299465
T3 - Proceedings of MobileHCI 2021 - ACM International Conference on Mobile Human-Computer Interaction: Mobile Apart, MobileTogether
BT - Proceedings of MobileHCI 2021 - ACM International Conference on Mobile Human-Computer Interaction
PB - Association for Computing Machinery, Inc
Y2 - 27 September 2021 through 1 October 2021
ER -